Paul Schrater

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 25

Top Topics

Information Foraging

Driven Learning

Image Synthesis

Top Venues

Publications

Arun Kumar, Paul Schrater
KIX: A Metacognitive Generalization Framework. CoRR (2024)
Itzel Olivos-Castillo, Paul Schrater, Xaq Pitkow
Control when confidence is costly. CoRR (2024)
Jong-Shenq Guo, Karen Guo, Paul Schrater
Prediction of human looking behavior using interest-based image representations. Commun. Inf. Syst. 23 (3) (2023)
Kara Kedrick, Paul Schrater, Wilma Koutstaal
The Multifaceted Role of Self-Generated Question Asking in Curiosity-Driven Learning. Cogn. Sci. 47 (4) (2023)
Thomas Gebhart, Jakob Hansen, Paul Schrater
Knowledge Sheaves: A Sheaf-Theoretic Framework for Knowledge Graph Embedding. AISTATS (2023)
Morteza Ansarinia, Paul Schrater, Pedro Cardoso-Leite
Linking Theories and Methods in Cognitive Sciences via Joint Embedding of the Scientific Literature: The Example of Cognitive Control. CogSci (2022)
Santiago Herce Castañón, Pedro Cardoso-Leite, C. Shawn Green, Daphne Bavelier, Paul Schrater
Optimal learning under structural environmental uncertainty reveals inherent learning trade-offs. CogSci (2022)
Morteza Ansarinia, Paul Schrater, Pedro Cardoso-Leite
Linking Theories and Methods in Cognitive Sciences via Joint Embedding of the Scientific Literature: The Example of Cognitive Control. CoRR (2022)
Kara Kedrick, Iris Vilares, Paul Schrater
The Generation of Original and Known Explanations: How the presence or absence of relevant information influences sense-making and information foraging. CogSci (2022)
Thomas Gebhart, Jakob Hansen, Paul Schrater
Knowledge Sheaves: A Sheaf-Theoretic Framework for Knowledge Graph Embedding. CoRR (2021)
Thomas Gebhart, Udit Saxena, Paul Schrater
A Unified Paths Perspective for Pruning at Initialization. CoRR (2021)
Kara Kedrick, Sashank Varma, Paul Schrater
Identifying Individual Differences in Sensemaking and Information Foraging. CogSci (2020)
Thomas Gebhart, Paul Schrater
Adversarial Examples Target Topological Holes in Deep Networks. CoRR (2019)
Rory Flemming, Emmanuel Schmück, Dominic Mussack, Pedro Cardoso-Leite, Paul Schrater
A generalizable performance evaluation model of driving games via risk-weighted trajectories. EDM (2019)
Thomas Gebhart, Paul Schrater, Alan Hylton
Characterizing the Shape of Activation Space in Deep Neural Networks. ICMLA (2019)
Gunnar Blohm, Paul Schrater, Konrad P. Körding
Ten Simple Rules for Organizing and Running a Successful Intensive Two-Week Course. Neural Comput. 31 (1) (2019)
Dominic Mussack, Rory Flemming, Paul Schrater, Pedro Cardoso-Leite
Towards discovering problem similarity through deep learning: combining problem features and user behavior. EDM (2019)
Emmanuel Schmück, Rory Flemming, Paul Schrater, Pedro Cardoso-Leite
Principles underlying the design of a cognitive training game as a research framework. VS-GAMES (2019)
S. Thomas Christie, Paul Schrater
Generating normative predictions with a variable-length rate code. CogSci (2019)
Dominic Mussack, Paul Schrater
Gradations in task engagement emerge from metacognitive priority control. CogSci (2019)
Yash Upadhyay, Paul Schrater
Generative Adversarial Network Architectures For Image Synthesis Using Capsule Networks. CoRR (2018)
Robert Edge, Dominic Mussack, Matthias Böhmer, Paul Schrater
Predicting Contextual Influences on App Usage from a Rational Model of Time Allocation. PerCom Workshops (2018)
Karen Guo, Danielle Pratt, Angus MacDonald III, Paul Schrater
Labeling Images by Interpretation from Natural Viewing. IUI Workshops (2018)
Thomas Gebhart, Paul Schrater
Adversary Detection in Neural Networks via Persistent Homology. CoRR (2017)
Karen Guo, Paul Schrater
Automatically Discovering Fatigue Patterns from Sparsely Labelled Temporal Data. ICMLA (2015)